Triple
T38502312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris (Robot Stories) |
E919871
|
entity |
| Predicate | appearsInAnthologyFilm |
P22734
|
FINISHED |
| Object | Robot Stories |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Robot Stories | Statement: [Iris (Robot Stories), appearsInAnthologyFilm, Robot Stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInAnthologyFilm Context triple: [Iris (Robot Stories), appearsInAnthologyFilm, Robot Stories]
-
A.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
B.
appearsInAdaptationBy
Indicates that an entity is featured or present in an adaptation created by a specified adapter (e.g., author, director, or studio).
-
C.
appearsInWrittenBy
Indicates that an entity (such as a character, concept, or element) appears in a written work that is authored by a specified creator.
-
D.
hasFictionalFilmWithinPlay
Indicates that within a theatrical play, there is a fictional film that exists or is depicted as part of the play’s narrative or structure.
-
E.
includedInFilm
chosen
Indicates that one entity (such as a scene, segment, or element) is contained within or forms part of a particular film.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e9ddd4481908f8c04439d848f9d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fef5cf8da881908260ec633830375d |
completed | May 9, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69fef455e40481909861c82007b79bc0 |
completed | May 9, 2026, 8:46 a.m. |
Created at: May 3, 2026, 4:31 p.m.